The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition

8 June 2021

Papers citing "The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition"

8 / 8 papers shown

Title
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D. Tiapkin Evgenii Chzhen Gilles Stoltz 74 0 0 08 Jul 2024
$A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds$ A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds Taira Tsuchiya Shinji Ito 26 0 0 30 May 2024
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond Christoph Dann Chen-Yu Wei Julian Zimmert 17 22 0 20 Feb 2023
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms Osama A. Hanna Lin F. Yang Christina Fragouli 19 11 0 08 Nov 2022
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds Shinji Ito Taira Tsuchiya Junya Honda AAML 13 16 0 14 Jun 2022
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs Chloé Rouyer Dirk van der Hoeven Nicolò Cesa-Bianchi Yevgeny Seldin 21 15 0 01 Jun 2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits Jiatai Huang Yan Dai Longbo Huang 12 14 0 28 Jan 2022
On Optimal Robustness to Adversarial Corruption in Online Decision Problems Shinji Ito 42 22 0 22 Sep 2021